- 一般社団法人 人工知能学会
- 人工知能学会論文誌 (ISSN:13460714)
- vol.35, no.1, pp.DSI-E_1-10, 2020-01-01 (Released:2020-01-01)
Understanding the various information from user utterances is important for chat-oriented dialogue systems. However, no study has yet clarified the types of information that should be understood by such systems. With this purpose in mind, we first collected information that humans perceive from each utterance (perceived information) in chat-oriented dialogue. We then categorized the types of perceived information. The types were evaluated on the basis of inter-annotator agreement, which showed substantial agreement and demonstrated the validity of our categorization. To the best of our knowledge, this study is the first attempt to clarify the types of information that a chat-oriented dialogue system should understand from varied user utterances.